6 papers
CUPA-T2*: Covariance-Aware Uncertainty Propagation and Alignment for T2* Mapping in Accelerated MRI
Gideon N. L. Rouwendaal, Natascha Niessen, Hannah Eichhorn +3
Quantitative T2* maps have strong potential for biomarker discovery but are limited by long scan times, rendering them impractical in clinical settings. Significant acceleration ca…
Gabor Primitives for Accelerated Cardiac Cine MRI Reconstruction
Wenqi Huang, Veronika Spieker, Nil Stolt-Ansó +6
Accelerated cardiac cine MRI requires reconstructing spatiotemporal images from highly undersampled k-space data. Implicit neural representations (INRs) enable scan-specific recons…
INR meets Multi-Contrast MRI Reconstruction
Natascha Niessen, Carolin M. Pirkl, Ana Beatriz Solana +6
Multi-contrast MRI sequences allow for the acquisition of images with varying tissue contrast within a single scan. The resulting multi-contrast images can be used to extract quant…
Motion-Robust T2* Quantification from Gradient Echo MRI with Physics-Informed Deep Learning
Hannah Eichhorn, Veronika Spieker, Kerstin Hammernik +5
Purpose: T2* quantification from gradient echo magnetic resonance imaging is particularly affected by subject motion due to the high sensitivity to magnetic field inhomogeneities,…
PISCO: Self-Supervised k-Space Regularization for Improved Neural Implicit k-Space Representations of Dynamic MRI
Veronika Spieker, Hannah Eichhorn, Wenqi Huang +9
Neural implicit k-space representations (NIK) have shown promising results for dynamic magnetic resonance imaging (MRI) at high temporal resolutions. Yet, reducing acquisition time…
Subspace Implicit Neural Representations for Real-Time Cardiac Cine MR Imaging
Wenqi Huang, Veronika Spieker, Siying Xu +6
Conventional cardiac cine MRI methods rely on retrospective gating, which limits temporal resolution and the ability to capture continuous cardiac dynamics, particularly in patient…